| Abstract: |
Artificial Neural Networks are used in a variety of problems occurring either in
research or in the industry. The first step is to train a network to perform a desired
function, which requires a training algorithm. Levenberg-Marquardt is a second order
algorithm which outperforms Backpropagation and is currently available in most Neural
Network toolboxes. This paper tests two toolboxes, Neural Network Toolbox of MatLab
and Neural Network System Identification Toolbox, in order to demonstrate that the
implementations differ according to the toolbox used and that Matlab obtains better
results in all the datasets used. This paper also explains the differences between the
implementations of each tool and the advantages/disadvantages of each toolbox. |
